






"""simple docstring"""


import gc
import unittest

from parameterized import parameterized

from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow


if is_flax_available():
		import jax
		import jax.numpy as jnp




@slow
@require_flax
class 						__UpperCamelCase     (     unittest.TestCase						):
					def        UpperCAmelCase__ (							self							:	Optional[int]     , UpperCAmelCase							:	Union[str, Any]     , UpperCAmelCase							:	Optional[Any]   )	->       List[Any]:
											return f"""gaussian_noise_s={seed}_shape={"_".join([str(UpperCAmelCase   ) for s in shape]   )}.npy"""
					def        UpperCAmelCase__ (							self							:	int   )	->       Dict:
											# clean up the VRAM after each test
											super().tearDown()
											gc.collect()
					def        UpperCAmelCase__ (							self							:	str     , UpperCAmelCase							:	str=0     , UpperCAmelCase							:	str=(4, 4, 64, 64)     , UpperCAmelCase							:	Optional[int]=False   )	->       Optional[int]:
											lowerCAmelCase   :List[str]						=			jnp.bfloataa if fpaa else jnp.floataa
											lowerCAmelCase   :Any						=			jnp.array(load_hf_numpy(self.get_file_format(UpperCAmelCase     , UpperCAmelCase   )   )     , dtype=UpperCAmelCase   )
											return image
					def        UpperCAmelCase__ (							self							:	List[Any]     , UpperCAmelCase							:	List[Any]=False     , UpperCAmelCase							:	List[str]="CompVis/stable-diffusion-v1-4"   )	->       List[str]:
											lowerCAmelCase   :List[str]						=			jnp.bfloataa if fpaa else jnp.floataa
											lowerCAmelCase   :Union[str, Any]						=			'bf16' if fpaa else None

											lowerCAmelCase	, lowerCAmelCase   :Optional[Any]						=			FlaxUNetaDConditionModel.from_pretrained(
											    UpperCAmelCase     , subfolder='unet'     , dtype=UpperCAmelCase     , revision=UpperCAmelCase   )
											return model, params
					def        UpperCAmelCase__ (							self							:	str     , UpperCAmelCase							:	Any=0     , UpperCAmelCase							:	str=(4, 77, 768)     , UpperCAmelCase							:	List[str]=False   )	->       Tuple:
											lowerCAmelCase   :List[str]						=			jnp.bfloataa if fpaa else jnp.floataa
											lowerCAmelCase   :Dict						=			jnp.array(load_hf_numpy(self.get_file_format(UpperCAmelCase     , UpperCAmelCase   )   )     , dtype=UpperCAmelCase   )
											return hidden_states
					@parameterized.expand(
					    [
					        # fmt: off
					        [83, 4, [-0.2_3_2_3, -0.1_3_0_4, 0.0_8_1_3, -0.3_0_9_3, -0.0_9_1_9, -0.1_5_7_1, -0.1_1_2_5, -0.5_8_0_6]],
					        [17, 0.5_5, [-0.0_8_3_1, -0.2_4_4_3, 0.0_9_0_1, -0.0_9_1_9, 0.3_3_9_6, 0.0_1_0_3, -0.3_7_4_3, 0.0_7_0_1]],
					        [8, 0.8_9, [-0.4_8_6_3, 0.0_8_5_9, 0.0_8_7_5, -0.1_6_5_8, 0.9_1_9_9, -0.0_1_1_4, 0.4_8_3_9, 0.4_6_3_9]],
					        [3, 1000, [-0.5_6_4_9, 0.2_4_0_2, -0.5_5_1_8, 0.1_2_4_8, 1.1_3_2_8, -0.2_4_4_3, -0.0_3_2_5, -1.0_0_7_8]],
					        # fmt: on
					    ]   )
					def        UpperCAmelCase__ (							self							:	Any     , UpperCAmelCase							:	str     , UpperCAmelCase							:	Tuple     , UpperCAmelCase							:	Optional[int]   )	->       Dict:
											lowerCAmelCase	, lowerCAmelCase   :Optional[Any]						=			self.get_unet_model(model_id='CompVis/stable-diffusion-v1-4'     , fpaa=UpperCAmelCase   )
											lowerCAmelCase   :Any						=			self.get_latents(UpperCAmelCase     , fpaa=UpperCAmelCase   )
											lowerCAmelCase   :Tuple						=			self.get_encoder_hidden_states(UpperCAmelCase     , fpaa=UpperCAmelCase   )

											lowerCAmelCase   :str						=			model.apply(
											    {'params': params}     , UpperCAmelCase     , jnp.array(UpperCAmelCase     , dtype=jnp.intaa   )     , encoder_hidden_states=UpperCAmelCase     , ).sample

											assert sample.shape == latents.shape

											lowerCAmelCase   :str						=			jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())   )     , dtype=jnp.floataa   )
											lowerCAmelCase   :Tuple						=			jnp.array(UpperCAmelCase     , dtype=jnp.floataa   )

											# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, in the same hardware
											assert jnp.allclose(UpperCAmelCase     , UpperCAmelCase     , atol=1e-2   )
					@parameterized.expand(
					    [
					        # fmt: off
					        [83, 4, [0.1_5_1_4, 0.0_8_0_7, 0.1_6_2_4, 0.1_0_1_6, -0.1_8_9_6, 0.0_2_6_3, 0.0_6_7_7, 0.2_3_1_0]],
					        [17, 0.5_5, [0.1_1_6_4, -0.0_2_1_6, 0.0_1_7_0, 0.1_5_8_9, -0.3_1_2_0, 0.1_0_0_5, -0.0_5_8_1, -0.1_4_5_8]],
					        [8, 0.8_9, [-0.1_7_5_8, -0.0_1_6_9, 0.1_0_0_4, -0.1_4_1_1, 0.1_3_1_2, 0.1_1_0_3, -0.1_9_9_6, 0.2_1_3_9]],
					        [3, 1000, [0.1_2_1_4, 0.0_3_5_2, -0.0_7_3_1, -0.1_5_6_2, -0.0_9_9_4, -0.0_9_0_6, -0.2_3_4_0, -0.0_5_3_9]],
					        # fmt: on
					    ]   )
					def        UpperCAmelCase__ (							self							:	int     , UpperCAmelCase							:	Any     , UpperCAmelCase							:	Optional[Any]     , UpperCAmelCase							:	Optional[int]   )	->       Union[str, Any]:
											lowerCAmelCase	, lowerCAmelCase   :Any						=			self.get_unet_model(model_id='stabilityai/stable-diffusion-2'     , fpaa=UpperCAmelCase   )
											lowerCAmelCase   :str						=			self.get_latents(UpperCAmelCase     , shape=(4, 4, 96, 96)     , fpaa=UpperCAmelCase   )
											lowerCAmelCase   :Tuple						=			self.get_encoder_hidden_states(UpperCAmelCase     , shape=(4, 77, 1024)     , fpaa=UpperCAmelCase   )

											lowerCAmelCase   :Optional[Any]						=			model.apply(
											    {'params': params}     , UpperCAmelCase     , jnp.array(UpperCAmelCase     , dtype=jnp.intaa   )     , encoder_hidden_states=UpperCAmelCase     , ).sample

											assert sample.shape == latents.shape

											lowerCAmelCase   :Optional[int]						=			jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())   )     , dtype=jnp.floataa   )
											lowerCAmelCase   :List[str]						=			jnp.array(UpperCAmelCase     , dtype=jnp.floataa   )

											# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, on the same hardware
											assert jnp.allclose(UpperCAmelCase     , UpperCAmelCase     , atol=1e-2   )







"""simple docstring"""


import itertools
import math


def        UpperCAmelCase      (					a__ ):





						'''simple docstring'''






						if 1 < number < 4:
												# 2 and 3 are primes
												return True
						elif number < 2 or number % 2 == 0 or number % 3 == 0:
												# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
												return False

						# All primes number are in format of 6k +/- 1
						for i in range(5     ,      int(math.sqrt(a__ ) + 1 )     ,      6 ):
												if number % i == 0 or number % (i + 2) == 0:
																		return False
						return True


def        UpperCAmelCase      (					):





						'''simple docstring'''






						lowerCAmelCase   :str						=			2
						while True:
												if is_prime(a__ ):
																		yield num
												num += 1


def        UpperCAmelCase      (					a__ = 1_00_01 ):





						'''simple docstring'''






						return next(itertools.islice(prime_generator()     ,      nth - 1     ,      a__ ) )


if __name__ == "__main__":
		print(F"""{solution() = }""")